Many websites track users' activities in order to measure website performance and improve users' experience. One method of tracking users' activities involves inserting analytics tags associated with website objects in web pages.
Current tag management systems facilitate the creation of analytics tags on a website. However, these current tag management systems utilize code-based tagging that requires knowledge of a website's HTML tags and CSS selectors to dynamically code the analytics tags. Thus, such existing analytics tagging techniques generally require technical sophistication to add code to insert analytics tagging functionality into website objects. While a website developer has such knowledge, the marketing personnel with responsibility for determining appropriate analytics tags generally do not. Therefore, marketing personnel can require the assistance of website developers to deploy analytics tags, which can lead to delays in the analytics tag deployment process.
Some prior solutions may automatically create analytics tagging code. However, these solutions still generally require some technical sophistication to identify different types of a website object to be tracked to ensure analytics tags are added to all types of the website object. For example, due to variability in the coding of websites, it is difficult for marketing personnel to identify and tag objects with similar or related functions (e.g., “Add to Cart,” “Add two items to cart,” “Buy Now,” and “Pay”) across multiple websites due to variations in object type (e.g., button, link, and image) and the specific code implementations for those functions in the different websites.
Current tag management systems do not adequately handle variations of objects in websites or propose additional relevant analytics tags.